Automatic CT Image Segmentation of the Lungs with Region Growing Algorithm
Computer aided diagnosis of lung CT image has been a revolutionary step in the early diagnosing of lung diseases. The best method of implementing computer aided diagnosis for medical image analysis is first to preprocess the image in order to segment it. The first step in computer aided diagnosis of lung computed tomography patient image is generally to first segment the region of interest, in this case lung, and then analyze separately each area obtained, for a tumor, cancer, node detection or other pathology for diagnosis. This is generally much easier approach, because the area used for setting the right diagnosis, is getting smaller with the process of segmentation, so the radiologist can focus his observation only on specific data inside the specific region. In this paper we proposed lung segmentation technique to accurately segment the lung parenchyma of lung CT images, which can help radiologist in early diagnosing lung diseases, but the algorithm can also be used to early diagnose other benign or malignant pathologies in other organs, such as liver, brain or spine.